1. Field of the Invention
The present invention relates to the field of image and video compression. More particularly, the present invention relates to a method and apparatus for improving the quality of compressed image and video signals while significantly reducing the complexity of post-processing in the image or video decoder.
2. Background Information
With the continuing growth of digital image and video technology in areas such as video telephony, where bandwidth is a scarce commodity, the demand for providing image compression while maintaining image quality is a compelling need. A digital image on a standard 640.times.480 pixel display screen requires an enormous amount of data. For example, assuming one byte per pixel for a gray scale digital image, the 640.times.480 pixel digital image occupies about 307,200 bytes of storage. A color digital image requires three bytes per pixel or about 921,600 bytes of storage. Today, display screens capable of displaying over 2000.times.2000 pixel images are readily available and require about twelve million bytes of data for a single color image. Even more demanding are motion videos which require even more data. The amount of data required to generate such images makes the storage, processing, and transmission of the data difficult. As a result, image compression, which reduces the amount of data required to represent a digital image, has evolved as an integral part in the storage and transmission of digital images.
In particular, source coding of image data has been a very active area of research for many years. The goal is to reduce the number of bits needed to represent an image while making as few perceptible changes to the image as possible. Typically, image and video compression algorithms employ a quantization stage. The effect of the quantization stage is to add quantization noise to the reconstructed image or video. Many algorithms have been developed which can successfully compress a gray scale image to approximately 0.8 bits per pixel ("bpp") with almost no perceptible effects. A problem arises, however, when these compression techniques are pushed beyond this rate. In implementing higher compression ratios (&lt;0.4 bpp for gray scale), typical algorithms generate artifacts which severely degrade the perceived (visual) quality of the image. The type of artifacts generated is dependent on the compression technique and on the particular image.
Recently, iterative techniques have been described for reducing the quantization noise effects associated with image and video encoding schemes that perform quantization. One approach is described by O'ROURKE & STEVENSON in Improved Image Decompression for Reduced Transform Coding Artifacts, IEEE TRANSACTIONS ON CIRCUIS AND SYSTEMS FOR VIDEO TECHNOLOGY, Vol. 5, Dec. 1995,490-99. This technique requires modification of an image decoder. Namely, the image decoder first obtains an initial estimate by decompressing the image. The initial estimate is applied to an iterative post processing filter which improves the initial estimate by successive iterations until the difference between successive estimates falls below a predetermined threshold or a maximum number of iterations is reached. Within each iteration of the post-processing filter, a step size is calculated in order to converge on an estimate. Although the iterative technique described in O'ROURKE & STEVENSON greatly reduces the noticeable artifacts which exist using standard decompression techniques, it has certain disadvantages associated with it.
First, the step size calculation apparatus for implementing such a technique is expensive and complex. Second, the entire image must be applied to the iterative post-processing filter because the step size for a particular iteration is dependent on the intermediate filtered image from the previous iteration. As such, the decoder will not be able to iteratively post-process a subsection of the image. Thirdly, since the entire image is applied to the iterative post-processing filter, the efficient exploitation of data cache locality in a computer based implementation will not be achieved.
Accordingly, there is need in the art for an apparatus and method of improving the quality of compressed image and video signals while reducing the complexity and cost of post-processing in the image or video decoder.